1.1 Trace plots for convergence check

The current MCMC setting is:

• 4000000 iteration;
  
• 3000000 burn-in;
  
• 1000 thinning.

1.2 Gelman and Rubin’s convergence check

## Potential scale reduction factors:
## 
##         Point est. Upper C.I.
## HDevsum      1.000      1.000
## LDevsum      1.000      1.003
## dh0          1.019      1.075
## dl0          1.022      1.103
## dl1          0.999      0.999
## 
## Multivariate psrf
## 
## 1.02

1.3 ACF Plots

Here we plotted ACF plots for the following variables:

• Total deviance;
  
• Variables that didn’t pass the convergence check.

1.4 WAIC results

2.1 Trace plots for convergence check

The current MCMC setting is:

• 4000000 iteration;
  
• 3000000 burn-in;
  
• 1000 thinning.

2.2 Gelman and Rubin’s convergence check

## Potential scale reduction factors:
## 
##         Point est. Upper C.I.
## HDevsum      0.999      0.999
## dh0          0.999      0.999
## 
## Multivariate psrf
## 
## 0.999

2.3 ACF Plots

Here we plotted ACF plots for the following variables:

• Total deviance;
  
• Variables that didn’t pass the convergence check.

2.4 WAIC results

3.1 Trace plots for convergence check

The current MCMC setting is:

• 4000000 iteration;
  
• 3000000 burn-in;
  
• 1000 thinning.

3.2 Gelman and Rubin’s convergence check

## Potential scale reduction factors:
## 
##         Point est. Upper C.I.
## LDevsum      1.000          1
## dl0          0.999          1
## dl1          1.001          1
## 
## Multivariate psrf
## 
## 1

3.3 ACF Plots

Here we plotted ACF plots for the following variables:

• Total deviance;
  
• Variables that didn’t pass the convergence check.

3.4 WAIC results